Overview

Dataset statistics

Number of variables17
Number of observations14259
Missing cells3707
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 MiB
Average record size in memory144.0 B

Variable types

Categorical6
Numeric6
Text4
DateTime1

Alerts

parent_region has constant value ""Constant
light is highly imbalanced (85.5%)Imbalance
weather_conditions has 3027 (21.2%) missing valuesMissing
address has 660 (4.6%) missing valuesMissing
temperature has 277 (1.9%) zerosZeros
wind_speed has 2925 (20.5%) zerosZeros
cloudiness has 2918 (20.5%) zerosZeros

Reproduction

Analysis started2024-01-10 15:17:16.644133
Analysis finished2024-01-10 15:17:23.866074
Duration7.22 seconds
Software versionydata-profiling vv4.6.2
Download configurationconfig.json

Variables

year
Categorical

Distinct5
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size222.8 KiB
2019.0
3529 
2020.0
3055 
2018.0
2684 
2021.0
2648 
2017.0
2342 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters85548
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021.0
2nd row2021.0
3rd row2021.0
4th row2021.0
5th row2020.0

Common Values

ValueCountFrequency (%)
2019.0 3529
24.7%
2020.0 3055
21.4%
2018.0 2684
18.8%
2021.0 2648
18.6%
2017.0 2342
16.4%
(Missing) 1
 
< 0.1%

Length

2024-01-10T18:17:23.966619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T18:17:24.085204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019.0 3529
24.8%
2020.0 3055
21.4%
2018.0 2684
18.8%
2021.0 2648
18.6%
2017.0 2342
16.4%

Most occurring characters

ValueCountFrequency (%)
0 31571
36.9%
2 19961
23.3%
. 14258
16.7%
1 11203
 
13.1%
9 3529
 
4.1%
8 2684
 
3.1%
7 2342
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71290
83.3%
Other Punctuation 14258
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31571
44.3%
2 19961
28.0%
1 11203
 
15.7%
9 3529
 
5.0%
8 2684
 
3.8%
7 2342
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 14258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85548
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31571
36.9%
2 19961
23.3%
. 14258
16.7%
1 11203
 
13.1%
9 3529
 
4.1%
8 2684
 
3.1%
7 2342
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31571
36.9%
2 19961
23.3%
. 14258
16.7%
1 11203
 
13.1%
9 3529
 
4.1%
8 2684
 
3.1%
7 2342
 
2.7%

month
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean7.1795483
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:24.206306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8
Q311
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)8

Descriptive statistics

Standard deviation3.8530957
Coefficient of variation (CV)0.53667661
Kurtosis-1.3970412
Mean7.1795483
Median Absolute Deviation (MAD)3
Skewness-0.32884043
Sum102366
Variance14.846346
MonotonicityNot monotonic
2024-01-10T18:17:24.316058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
11 2073
14.5%
12 1817
12.7%
10 1736
12.2%
1 1506
10.6%
9 1305
9.2%
2 1200
8.4%
3 1105
7.7%
8 904
6.3%
4 760
 
5.3%
7 671
 
4.7%
Other values (2) 1181
8.3%
ValueCountFrequency (%)
1 1506
10.6%
2 1200
8.4%
3 1105
7.7%
4 760
5.3%
5 622
 
4.4%
6 559
 
3.9%
7 671
 
4.7%
8 904
6.3%
9 1305
9.2%
10 1736
12.2%
ValueCountFrequency (%)
12 1817
12.7%
11 2073
14.5%
10 1736
12.2%
9 1305
9.2%
8 904
6.3%
7 671
 
4.7%
6 559
 
3.9%
5 622
 
4.4%
4 760
 
5.3%
3 1105
7.7%

temperature
Real number (ℝ)

ZEROS 

Distinct500
Distinct (%)3.5%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4.7320191
Minimum-27.7
Maximum32
Zeros277
Zeros (%)1.9%
Negative4071
Negative (%)28.6%
Memory size222.8 KiB
2024-01-10T18:17:24.445251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-27.7
5-th percentile-9
Q1-1
median3.1
Q311.375
95-th percentile19.9
Maximum32
Range59.7
Interquartile range (IQR)12.375

Descriptive statistics

Standard deviation8.911348
Coefficient of variation (CV)1.883202
Kurtosis-0.23500387
Mean4.7320191
Median Absolute Deviation (MAD)5.7
Skewness0.12261362
Sum67450.2
Variance79.412123
MonotonicityNot monotonic
2024-01-10T18:17:24.591386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 403
 
2.8%
1 334
 
2.3%
0 277
 
1.9%
3 256
 
1.8%
-2 233
 
1.6%
-1 230
 
1.6%
5 208
 
1.5%
9 179
 
1.3%
4 160
 
1.1%
7 153
 
1.1%
Other values (490) 11821
82.9%
ValueCountFrequency (%)
-27.7 1
< 0.1%
-27.4 1
< 0.1%
-27.2 1
< 0.1%
-26.8 1
< 0.1%
-26.7 1
< 0.1%
-26.4 1
< 0.1%
-26.3 1
< 0.1%
-26.2 1
< 0.1%
-25.3 1
< 0.1%
-25 2
< 0.1%
ValueCountFrequency (%)
32 1
 
< 0.1%
31.2 1
 
< 0.1%
31 1
 
< 0.1%
30.4 2
 
< 0.1%
30 1
 
< 0.1%
29.9 1
 
< 0.1%
29.7 2
 
< 0.1%
29 5
< 0.1%
28.8 1
 
< 0.1%
28.5 2
 
< 0.1%

atmospheric_pressure
Real number (ℝ)

Distinct486
Distinct (%)3.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean761.73237
Minimum724.7
Maximum787.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:24.733253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum724.7
5-th percentile748.5
Q1756.7
median761.5
Q3766.8
95-th percentile775.5
Maximum787.4
Range62.7
Interquartile range (IQR)10.1

Descriptive statistics

Standard deviation8.1638682
Coefficient of variation (CV)0.010717502
Kurtosis0.47223358
Mean761.73237
Median Absolute Deviation (MAD)5.1
Skewness0.0041896556
Sum10860780
Variance66.648743
MonotonicityNot monotonic
2024-01-10T18:17:24.874503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
758.2 255
 
1.8%
759.7 237
 
1.7%
762.8 233
 
1.6%
761.2 225
 
1.6%
759 222
 
1.6%
763.5 215
 
1.5%
765 202
 
1.4%
757.7 196
 
1.4%
766.6 191
 
1.3%
764.3 187
 
1.3%
Other values (476) 12095
84.8%
ValueCountFrequency (%)
724.7 1
 
< 0.1%
725.4 1
 
< 0.1%
725.9 2
< 0.1%
729 1
 
< 0.1%
729.7 2
< 0.1%
730 2
< 0.1%
730.4 1
 
< 0.1%
730.5 3
< 0.1%
733.8 1
 
< 0.1%
735.1 1
 
< 0.1%
ValueCountFrequency (%)
787.4 1
 
< 0.1%
786.9 2
< 0.1%
786.8 1
 
< 0.1%
786.7 3
< 0.1%
786.6 1
 
< 0.1%
786.1 3
< 0.1%
785.8 1
 
< 0.1%
785.6 1
 
< 0.1%
785.5 1
 
< 0.1%
785.4 2
< 0.1%

humidity
Real number (ℝ)

Distinct81
Distinct (%)0.6%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean79.034659
Minimum19
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:25.036176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile48
Q171
median83
Q391
95-th percentile97
Maximum100
Range81
Interquartile range (IQR)20

Descriptive statistics

Standard deviation15.288426
Coefficient of variation (CV)0.19343951
Kurtosis0.6910522
Mean79.034659
Median Absolute Deviation (MAD)9
Skewness-1.0608264
Sum1126481
Variance233.73596
MonotonicityNot monotonic
2024-01-10T18:17:25.197088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
93 1044
 
7.3%
87 722
 
5.1%
86 604
 
4.2%
94 529
 
3.7%
88 497
 
3.5%
100 468
 
3.3%
92 427
 
3.0%
81 412
 
2.9%
90 398
 
2.8%
80 396
 
2.8%
Other values (71) 8756
61.4%
ValueCountFrequency (%)
19 2
 
< 0.1%
20 1
 
< 0.1%
22 3
 
< 0.1%
23 4
 
< 0.1%
24 2
 
< 0.1%
25 8
0.1%
26 5
 
< 0.1%
27 8
0.1%
28 16
0.1%
29 9
0.1%
ValueCountFrequency (%)
100 468
3.3%
99 20
 
0.1%
98 54
 
0.4%
97 201
 
1.4%
96 263
 
1.8%
95 317
 
2.2%
94 529
3.7%
93 1044
7.3%
92 427
3.0%
91 363
 
2.5%
Distinct18
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size222.8 KiB
Штиль, безветрие
2928 
Ю
1335 
ЮЮВ
1249 
З
1230 
ЮВ
936 
Other values (13)
6580 

Length

Max length22
Median length16
Mean length5.1218965
Min length1

Characters and Unicode

Total characters73028
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowВ
2nd rowВ
3rd rowШтиль, безветрие
4th rowССЗ
5th rowШтиль, безветрие

Common Values

ValueCountFrequency (%)
Штиль, безветрие 2928
20.5%
Ю 1335
9.4%
ЮЮВ 1249
8.8%
З 1230
 
8.6%
ЮВ 936
 
6.6%
ЗЮЗ 880
 
6.2%
ЗСЗ 693
 
4.9%
ЮЗ 659
 
4.6%
ЮЮЗ 631
 
4.4%
СЗ 628
 
4.4%
Other values (8) 3089
21.7%

Length

2024-01-10T18:17:25.338048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
штиль 2928
16.9%
безветрие 2928
16.9%
ю 1335
 
7.7%
ююв 1249
 
7.2%
з 1230
 
7.1%
юв 936
 
5.4%
зюз 880
 
5.1%
зсз 693
 
4.0%
юз 659
 
3.8%
ююз 631
 
3.6%
Other values (10) 3825
22.1%

Most occurring characters

ValueCountFrequency (%)
е 9432
12.9%
Ю 8077
11.1%
З 6846
 
9.4%
и 5964
 
8.2%
т 5856
 
8.0%
В 4839
 
6.6%
С 4042
 
5.5%
р 3144
 
4.3%
л 3036
 
4.2%
3036
 
4.2%
Other values (12) 18756
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40224
55.1%
Uppercase Letter 26840
36.8%
Space Separator 3036
 
4.2%
Other Punctuation 2928
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
е 9432
23.4%
и 5964
14.8%
т 5856
14.6%
р 3144
 
7.8%
л 3036
 
7.5%
в 3036
 
7.5%
з 2928
 
7.3%
б 2928
 
7.3%
ь 2928
 
7.3%
н 432
 
1.1%
Other values (4) 540
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
Ю 8077
30.1%
З 6846
25.5%
В 4839
18.0%
С 4042
15.1%
Ш 2928
 
10.9%
П 108
 
0.4%
Space Separator
ValueCountFrequency (%)
3036
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2928
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 67064
91.8%
Common 5964
 
8.2%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
е 9432
14.1%
Ю 8077
12.0%
З 6846
10.2%
и 5964
8.9%
т 5856
8.7%
В 4839
 
7.2%
С 4042
 
6.0%
р 3144
 
4.7%
л 3036
 
4.5%
в 3036
 
4.5%
Other values (10) 12792
19.1%
Common
ValueCountFrequency (%)
3036
50.9%
, 2928
49.1%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 67064
91.8%
ASCII 5964
 
8.2%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
е 9432
14.1%
Ю 8077
12.0%
З 6846
10.2%
и 5964
8.9%
т 5856
8.7%
В 4839
 
7.2%
С 4042
 
6.0%
р 3144
 
4.7%
л 3036
 
4.5%
в 3036
 
4.5%
Other values (10) 12792
19.1%
ASCII
ValueCountFrequency (%)
3036
50.9%
, 2928
49.1%

wind_speed
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)0.1%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.8254647
Minimum0
Maximum13
Zeros2925
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:25.449937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q33
95-th percentile5
Maximum13
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7269348
Coefficient of variation (CV)0.94602471
Kurtosis2.5706051
Mean1.8254647
Median Absolute Deviation (MAD)1
Skewness1.4576878
Sum26022
Variance2.9823037
MonotonicityNot monotonic
2024-01-10T18:17:25.569031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 4807
33.7%
0 2925
20.5%
2 2900
20.3%
3 1510
 
10.6%
4 902
 
6.3%
5 535
 
3.8%
6 361
 
2.5%
7 178
 
1.2%
8 79
 
0.6%
9 40
 
0.3%
Other values (4) 18
 
0.1%
ValueCountFrequency (%)
0 2925
20.5%
1 4807
33.7%
2 2900
20.3%
3 1510
 
10.6%
4 902
 
6.3%
5 535
 
3.8%
6 361
 
2.5%
7 178
 
1.2%
8 79
 
0.6%
9 40
 
0.3%
ValueCountFrequency (%)
13 1
 
< 0.1%
12 5
 
< 0.1%
11 5
 
< 0.1%
10 7
 
< 0.1%
9 40
 
0.3%
8 79
 
0.6%
7 178
 
1.2%
6 361
2.5%
5 535
3.8%
4 902
6.3%

cloudiness
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.68522233
Minimum0
Maximum1
Zeros2918
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:25.695942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.4
median0.95
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.40145465
Coefficient of variation (CV)0.58587503
Kurtosis-0.97762388
Mean0.68522233
Median Absolute Deviation (MAD)0.05
Skewness-0.85121633
Sum9769.9
Variance0.16116584
MonotonicityNot monotonic
2024-01-10T18:17:25.809504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 6786
47.6%
0 2918
20.5%
0.75 1867
 
13.1%
0.95 929
 
6.5%
0.25 429
 
3.0%
0.45 425
 
3.0%
0.6 364
 
2.6%
0.4 260
 
1.8%
0.5 111
 
0.8%
0.2 104
 
0.7%
Other values (2) 65
 
0.5%
ValueCountFrequency (%)
0 2918
20.5%
0.05 52
 
0.4%
0.1 13
 
0.1%
0.2 104
 
0.7%
0.25 429
 
3.0%
0.4 260
 
1.8%
0.45 425
 
3.0%
0.5 111
 
0.8%
0.6 364
 
2.6%
0.75 1867
13.1%
ValueCountFrequency (%)
1 6786
47.6%
0.95 929
 
6.5%
0.75 1867
 
13.1%
0.6 364
 
2.6%
0.5 111
 
0.8%
0.45 425
 
3.0%
0.4 260
 
1.8%
0.25 429
 
3.0%
0.2 104
 
0.7%
0.1 13
 
0.1%

weather_conditions
Text

MISSING 

Distinct94
Distinct (%)0.8%
Missing3027
Missing (%)21.2%
Memory size222.8 KiB
2024-01-10T18:17:25.938029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length132
Median length111
Mean length17.002582
Min length1

Characters and Unicode

Total characters190973
Distinct characters51
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.2%

Sample

1st rowСостояние неба в общем не изменилось.
2nd row
3rd row
4th row
5th rowДымка.
ValueCountFrequency (%)
в 2532
 
10.2%
дымка 2109
 
8.5%
срок 1843
 
7.4%
наблюдения 1843
 
7.4%
снег 1633
 
6.6%
слабый 1275
 
5.1%
непрерывный 1142
 
4.6%
дождь 1045
 
4.2%
слабый(ая)(ые 829
 
3.3%
или 827
 
3.3%
Other values (114) 9793
39.4%
2024-01-10T18:17:26.245281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28978
15.2%
е 15785
 
8.3%
н 14231
 
7.5%
а 11689
 
6.1%
ы 10271
 
5.4%
и 9365
 
4.9%
л 7444
 
3.9%
с 7396
 
3.9%
о 7386
 
3.9%
в 6663
 
3.5%
Other values (41) 71765
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 143295
75.0%
Space Separator 28978
 
15.2%
Uppercase Letter 6035
 
3.2%
Other Punctuation 5335
 
2.8%
Close Punctuation 3650
 
1.9%
Open Punctuation 3650
 
1.9%
Decimal Number 30
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
е 15785
 
11.0%
н 14231
 
9.9%
а 11689
 
8.2%
ы 10271
 
7.2%
и 9365
 
6.5%
л 7444
 
5.2%
с 7396
 
5.2%
о 7386
 
5.2%
в 6663
 
4.6%
й 6164
 
4.3%
Other values (20) 46901
32.7%
Uppercase Letter
ValueCountFrequency (%)
Д 2678
44.4%
С 2319
38.4%
Л 797
 
13.2%
М 86
 
1.4%
О 67
 
1.1%
Г 33
 
0.5%
Т 31
 
0.5%
З 22
 
0.4%
Ч 1
 
< 0.1%
В 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 13
43.3%
1 7
23.3%
2 4
 
13.3%
4 3
 
10.0%
5 3
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 4916
92.1%
, 405
 
7.6%
/ 14
 
0.3%
Space Separator
ValueCountFrequency (%)
28978
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3650
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3650
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 149330
78.2%
Common 41643
 
21.8%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
е 15785
 
10.6%
н 14231
 
9.5%
а 11689
 
7.8%
ы 10271
 
6.9%
и 9365
 
6.3%
л 7444
 
5.0%
с 7396
 
5.0%
о 7386
 
4.9%
в 6663
 
4.5%
й 6164
 
4.1%
Other values (30) 52936
35.4%
Common
ValueCountFrequency (%)
28978
69.6%
. 4916
 
11.8%
) 3650
 
8.8%
( 3650
 
8.8%
, 405
 
1.0%
/ 14
 
< 0.1%
3 13
 
< 0.1%
1 7
 
< 0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 149330
78.2%
ASCII 41643
 
21.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28978
69.6%
. 4916
 
11.8%
) 3650
 
8.8%
( 3650
 
8.8%
, 405
 
1.0%
/ 14
 
< 0.1%
3 13
 
< 0.1%
1 7
 
< 0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
Cyrillic
ValueCountFrequency (%)
е 15785
 
10.6%
н 14231
 
9.5%
а 11689
 
7.8%
ы 10271
 
6.9%
и 9365
 
6.3%
л 7444
 
5.0%
с 7396
 
5.0%
о 7386
 
4.9%
в 6663
 
4.5%
й 6164
 
4.1%
Other values (30) 52936
35.4%

light
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
В темное время суток, освещение включено
13658 
Сумерки
 
483
В темное время суток, освещение не включено
 
59
В темное время суток, освещение отсутствует
 
59

Length

Max length43
Median length40
Mean length38.907006
Min length7

Characters and Unicode

Total characters554775
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowВ темное время суток, освещение включено
2nd rowВ темное время суток, освещение включено
3rd rowВ темное время суток, освещение включено
4th rowВ темное время суток, освещение не включено
5th rowВ темное время суток, освещение включено

Common Values

ValueCountFrequency (%)
В темное время суток, освещение включено 13658
95.8%
Сумерки 483
 
3.4%
В темное время суток, освещение не включено 59
 
0.4%
В темное время суток, освещение отсутствует 59
 
0.4%

Length

2024-01-10T18:17:26.384616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T18:17:26.503493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
в 13776
16.6%
темное 13776
16.6%
время 13776
16.6%
суток 13776
16.6%
освещение 13776
16.6%
включено 13717
16.5%
сумерки 483
 
0.6%
не 59
 
0.1%
отсутствует 59
 
0.1%

Most occurring characters

ValueCountFrequency (%)
е 96974
17.5%
68939
12.4%
о 55104
9.9%
н 41328
 
7.4%
в 41328
 
7.4%
м 28035
 
5.1%
к 27976
 
5.0%
т 27788
 
5.0%
с 27670
 
5.0%
у 14377
 
2.6%
Other values (10) 125256
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 457801
82.5%
Space Separator 68939
 
12.4%
Uppercase Letter 14259
 
2.6%
Other Punctuation 13776
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
е 96974
21.2%
о 55104
12.0%
н 41328
9.0%
в 41328
9.0%
м 28035
 
6.1%
к 27976
 
6.1%
т 27788
 
6.1%
с 27670
 
6.0%
у 14377
 
3.1%
р 14259
 
3.1%
Other values (6) 82962
18.1%
Uppercase Letter
ValueCountFrequency (%)
В 13776
96.6%
С 483
 
3.4%
Space Separator
ValueCountFrequency (%)
68939
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13776
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 472060
85.1%
Common 82715
 
14.9%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
е 96974
20.5%
о 55104
11.7%
н 41328
8.8%
в 41328
8.8%
м 28035
 
5.9%
к 27976
 
5.9%
т 27788
 
5.9%
с 27670
 
5.9%
у 14377
 
3.0%
р 14259
 
3.0%
Other values (8) 97221
20.6%
Common
ValueCountFrequency (%)
68939
83.3%
, 13776
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 472060
85.1%
ASCII 82715
 
14.9%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
е 96974
20.5%
о 55104
11.7%
н 41328
8.8%
в 41328
8.8%
м 28035
 
5.9%
к 27976
 
5.9%
т 27788
 
5.9%
с 27670
 
5.9%
у 14377
 
3.0%
р 14259
 
3.0%
Other values (8) 97221
20.6%
ASCII
ValueCountFrequency (%)
68939
83.3%
, 13776
 
16.7%

point
Text

Distinct13907
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:26.701570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length37
Mean length36.322673
Min length27

Characters and Unicode

Total characters517925
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13782 ?
Unique (%)96.7%

Sample

1st row{'lat': 55.667499, 'long': 37.770245}
2nd row{'lat': 55.669411, 'long': 37.553995}
3rd row{'lat': 55.7174, 'long': 37.568661}
4th row{'lat': 55.447467, 'long': 37.133403}
5th row{'lat': 55.844982, 'long': 37.424455}
ValueCountFrequency (%)
lat 14259
25.0%
long 14259
25.0%
55.0 17
 
< 0.1%
37.0 16
 
< 0.1%
37.839 14
 
< 0.1%
55.864 13
 
< 0.1%
55.893 13
 
< 0.1%
55.883 12
 
< 0.1%
55.875 12
 
< 0.1%
55.874 12
 
< 0.1%
Other values (24585) 28409
49.8%
2024-01-10T18:17:27.029418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 57036
 
11.0%
5 46878
 
9.1%
42777
 
8.3%
7 35363
 
6.8%
3 28923
 
5.6%
l 28518
 
5.5%
: 28518
 
5.5%
. 28516
 
5.5%
6 20049
 
3.9%
8 19168
 
3.7%
Other values (15) 182179
35.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 218480
42.2%
Other Punctuation 128329
24.8%
Lowercase Letter 99819
19.3%
Space Separator 42777
 
8.3%
Close Punctuation 14259
 
2.8%
Open Punctuation 14259
 
2.8%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 46878
21.5%
7 35363
16.2%
3 28923
13.2%
6 20049
9.2%
8 19168
8.8%
4 16605
 
7.6%
9 13881
 
6.4%
1 13599
 
6.2%
2 13593
 
6.2%
0 10421
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
l 28518
28.6%
n 14261
14.3%
o 14261
14.3%
g 14259
14.3%
t 14259
14.3%
a 14259
14.3%
e 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
' 57036
44.4%
: 28518
22.2%
. 28516
22.2%
, 14259
 
11.1%
Space Separator
ValueCountFrequency (%)
42777
100.0%
Close Punctuation
ValueCountFrequency (%)
} 14259
100.0%
Open Punctuation
ValueCountFrequency (%)
{ 14259
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 418104
80.7%
Latin 99821
 
19.3%

Most frequent character per script

Common
ValueCountFrequency (%)
' 57036
13.6%
5 46878
11.2%
42777
10.2%
7 35363
 
8.5%
3 28923
 
6.9%
: 28518
 
6.8%
. 28516
 
6.8%
6 20049
 
4.8%
8 19168
 
4.6%
4 16605
 
4.0%
Other values (7) 94271
22.5%
Latin
ValueCountFrequency (%)
l 28518
28.6%
n 14261
14.3%
o 14261
14.3%
g 14259
14.3%
t 14259
14.3%
a 14259
14.3%
N 2
 
< 0.1%
e 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517925
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 57036
 
11.0%
5 46878
 
9.1%
42777
 
8.3%
7 35363
 
6.8%
3 28923
 
5.6%
l 28518
 
5.5%
: 28518
 
5.5%
. 28516
 
5.5%
6 20049
 
3.9%
8 19168
 
3.7%
Other values (15) 182179
35.2%

pogoda_region
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
Восток
2086 
Юг
1903 
Запад
1888 
Север
1795 
Северо-восток
1764 
Other values (4)
4823 

Length

Max length13
Median length10
Mean length7.0902588
Min length2

Characters and Unicode

Total characters101100
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowЮго-восток
2nd rowЮго-запад
3rd rowЦентр
4th rowСеверо-запад
5th rowСеверо-запад

Common Values

ValueCountFrequency (%)
Восток 2086
14.6%
Юг 1903
13.3%
Запад 1888
13.2%
Север 1795
12.6%
Северо-восток 1764
12.4%
Северо-запад 1313
9.2%
Центр 1267
8.9%
Юго-восток 1153
8.1%
Юго-запад 1090
7.6%

Length

2024-01-10T18:17:27.170014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T18:17:27.301999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
восток 2086
14.6%
юг 1903
13.3%
запад 1888
13.2%
север 1795
12.6%
северо-восток 1764
12.4%
северо-запад 1313
9.2%
центр 1267
8.9%
юго-восток 1153
8.1%
юго-запад 1090
7.6%

Most occurring characters

ValueCountFrequency (%)
о 15326
15.2%
е 11011
10.9%
а 8582
 
8.5%
в 7789
 
7.7%
т 6270
 
6.2%
р 6139
 
6.1%
- 5320
 
5.3%
с 5003
 
4.9%
к 5003
 
4.9%
С 4872
 
4.8%
Other values (9) 25785
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 81521
80.6%
Uppercase Letter 14259
 
14.1%
Dash Punctuation 5320
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 15326
18.8%
е 11011
13.5%
а 8582
10.5%
в 7789
9.6%
т 6270
7.7%
р 6139
7.5%
с 5003
 
6.1%
к 5003
 
6.1%
п 4291
 
5.3%
д 4291
 
5.3%
Other values (3) 7816
9.6%
Uppercase Letter
ValueCountFrequency (%)
С 4872
34.2%
Ю 4146
29.1%
В 2086
14.6%
З 1888
 
13.2%
Ц 1267
 
8.9%
Dash Punctuation
ValueCountFrequency (%)
- 5320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 95780
94.7%
Common 5320
 
5.3%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 15326
16.0%
е 11011
11.5%
а 8582
 
9.0%
в 7789
 
8.1%
т 6270
 
6.5%
р 6139
 
6.4%
с 5003
 
5.2%
к 5003
 
5.2%
С 4872
 
5.1%
п 4291
 
4.5%
Other values (8) 21494
22.4%
Common
ValueCountFrequency (%)
- 5320
100.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 95780
94.7%
ASCII 5320
 
5.3%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 15326
16.0%
е 11011
11.5%
а 8582
 
9.0%
в 7789
 
8.1%
т 6270
 
6.5%
р 6139
 
6.4%
с 5003
 
5.2%
к 5003
 
5.2%
С 4872
 
5.1%
п 4291
 
4.5%
Other values (8) 21494
22.4%
ASCII
ValueCountFrequency (%)
- 5320
100.0%

region
Text

Distinct121
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
2024-01-10T18:17:27.474539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length11.608388
Min length5

Characters and Unicode

Total characters165524
Distinct characters58
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowЛюблино
2nd rowЧеремушки
3rd rowХамовники
4th rowЮжное Тушино
5th rowЮжное Тушино
ValueCountFrequency (%)
северное 807
 
4.7%
южное 762
 
4.4%
тушино 402
 
2.3%
измайлово 393
 
2.3%
чертаново 382
 
2.2%
восточное 351
 
2.0%
бирюлево 300
 
1.8%
орехово-борисово 277
 
1.6%
пресненский 264
 
1.5%
гольяново 251
 
1.5%
Other values (113) 12945
75.6%
2024-01-10T18:17:27.781865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
о 26434
16.0%
е 14185
 
8.6%
и 12643
 
7.6%
н 12276
 
7.4%
в 11005
 
6.6%
к 9167
 
5.5%
р 8392
 
5.1%
а 7824
 
4.7%
с 7242
 
4.4%
й 5036
 
3.0%
Other values (48) 51320
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 142313
86.0%
Uppercase Letter 18533
 
11.2%
Space Separator 2875
 
1.7%
Dash Punctuation 1803
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 26434
18.6%
е 14185
10.0%
и 12643
8.9%
н 12276
8.6%
в 11005
 
7.7%
к 9167
 
6.4%
р 8392
 
5.9%
а 7824
 
5.5%
с 7242
 
5.1%
й 5036
 
3.5%
Other values (21) 28109
19.8%
Uppercase Letter
ValueCountFrequency (%)
С 2225
 
12.0%
М 1718
 
9.3%
Б 1667
 
9.0%
Т 1225
 
6.6%
Д 997
 
5.4%
П 953
 
5.1%
К 949
 
5.1%
В 929
 
5.0%
Н 909
 
4.9%
О 858
 
4.6%
Other values (15) 6103
32.9%
Space Separator
ValueCountFrequency (%)
2875
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 160846
97.2%
Common 4678
 
2.8%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 26434
16.4%
е 14185
 
8.8%
и 12643
 
7.9%
н 12276
 
7.6%
в 11005
 
6.8%
к 9167
 
5.7%
р 8392
 
5.2%
а 7824
 
4.9%
с 7242
 
4.5%
й 5036
 
3.1%
Other values (46) 46642
29.0%
Common
ValueCountFrequency (%)
2875
61.5%
- 1803
38.5%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 160846
97.2%
ASCII 4678
 
2.8%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 26434
16.4%
е 14185
 
8.8%
и 12643
 
7.9%
н 12276
 
7.6%
в 11005
 
6.8%
к 9167
 
5.7%
р 8392
 
5.2%
а 7824
 
4.9%
с 7242
 
4.5%
й 5036
 
3.1%
Other values (46) 46642
29.0%
ASCII
ValueCountFrequency (%)
2875
61.5%
- 1803
38.5%

address
Text

MISSING 

Distinct9301
Distinct (%)68.4%
Missing660
Missing (%)4.6%
Memory size222.8 KiB
2024-01-10T18:17:28.003830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length108
Median length89
Mean length36.990808
Min length19

Characters and Unicode

Total characters503038
Distinct characters84
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7344 ?
Unique (%)54.0%

Sample

1st rowг Москва, ул Верхние Поля, 39
2nd rowг Москва, ул Профсоюзная, 56
3rd rowг Москва, пр-кт Комсомольский, 48
4th rowА-113 Центральная кольцевая автомобильная дорога (Московская область), 239 км
5th rowг Москва, ул Туристская, 2
ValueCountFrequency (%)
москва 13015
 
15.3%
г 12989
 
15.2%
ул 6861
 
8.1%
ш 1938
 
2.3%
км 1881
 
2.2%
мкад 1713
 
2.0%
сторона 1690
 
2.0%
дорога 1624
 
1.9%
автомобильная 1623
 
1.9%
кольцевая 1623
 
1.9%
Other values (2783) 40226
47.2%
2024-01-10T18:17:28.383743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71587
 
14.2%
о 43420
 
8.6%
а 37906
 
7.5%
к 33357
 
6.6%
с 29165
 
5.8%
, 27744
 
5.5%
в 27154
 
5.4%
М 17868
 
3.6%
г 16424
 
3.3%
р 15204
 
3.0%
Other values (74) 183209
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 328029
65.2%
Space Separator 71587
 
14.2%
Uppercase Letter 37936
 
7.5%
Other Punctuation 29662
 
5.9%
Decimal Number 29350
 
5.8%
Dash Punctuation 3006
 
0.6%
Open Punctuation 1728
 
0.3%
Close Punctuation 1728
 
0.3%
Other Symbol 11
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 43420
13.2%
а 37906
11.6%
к 33357
10.2%
с 29165
 
8.9%
в 27154
 
8.3%
г 16424
 
5.0%
р 15204
 
4.6%
н 15132
 
4.6%
л 14842
 
4.5%
я 14324
 
4.4%
Other values (25) 81101
24.7%
Uppercase Letter
ValueCountFrequency (%)
М 17868
47.1%
К 3690
 
9.7%
А 2807
 
7.4%
Д 2297
 
6.1%
С 1427
 
3.8%
Б 1379
 
3.6%
В 1271
 
3.4%
П 1134
 
3.0%
Л 938
 
2.5%
Н 636
 
1.7%
Other values (19) 4489
 
11.8%
Decimal Number
ValueCountFrequency (%)
1 7573
25.8%
2 4734
16.1%
3 3181
10.8%
4 2607
 
8.9%
5 2237
 
7.6%
6 2208
 
7.5%
8 1781
 
6.1%
7 1780
 
6.1%
9 1626
 
5.5%
0 1623
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 27744
93.5%
. 1898
 
6.4%
" 20
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3005
> 99.9%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
71587
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1728
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1728
100.0%
Other Symbol
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 365960
72.7%
Common 137073
 
27.2%
Latin 5
 
< 0.1%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 43420
 
11.9%
а 37906
 
10.4%
к 33357
 
9.1%
с 29165
 
8.0%
в 27154
 
7.4%
М 17868
 
4.9%
г 16424
 
4.5%
р 15204
 
4.2%
н 15132
 
4.1%
л 14842
 
4.1%
Other values (51) 115488
31.6%
Common
ValueCountFrequency (%)
71587
52.2%
, 27744
 
20.2%
1 7573
 
5.5%
2 4734
 
3.5%
3 3181
 
2.3%
- 3005
 
2.2%
4 2607
 
1.9%
5 2237
 
1.6%
6 2208
 
1.6%
. 1898
 
1.4%
Other values (10) 10299
 
7.5%
Latin
ValueCountFrequency (%)
c 3
60.0%
r 1
 
20.0%
A 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 365960
72.7%
ASCII 137066
 
27.2%
Letterlike Symbols 11
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71587
52.2%
, 27744
 
20.2%
1 7573
 
5.5%
2 4734
 
3.5%
3 3181
 
2.3%
- 3005
 
2.2%
4 2607
 
1.9%
5 2237
 
1.6%
6 2208
 
1.6%
. 1898
 
1.4%
Other values (11) 10292
 
7.5%
Cyrillic
ValueCountFrequency (%)
о 43420
 
11.9%
а 37906
 
10.4%
к 33357
 
9.1%
с 29165
 
8.0%
в 27154
 
7.4%
М 17868
 
4.9%
г 16424
 
4.5%
р 15204
 
4.2%
н 15132
 
4.1%
л 14842
 
4.1%
Other values (51) 115488
31.6%
Letterlike Symbols
ValueCountFrequency (%)
11
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%
Distinct13836
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
Minimum2016-12-31 22:50:00
Maximum2021-11-30 23:02:00
2024-01-10T18:17:28.519906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:28.666917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

severity
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
Легкий
10397 
Тяжёлый
3085 
С погибшими
 
777

Length

Max length11
Median length6
Mean length6.4888141
Min length6

Characters and Unicode

Total characters92524
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowЛегкий
2nd rowЛегкий
3rd rowЛегкий
4th rowТяжёлый
5th rowЛегкий

Common Values

ValueCountFrequency (%)
Легкий 10397
72.9%
Тяжёлый 3085
 
21.6%
С погибшими 777
 
5.4%

Length

2024-01-10T18:17:28.813515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T18:17:28.923378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
легкий 10397
69.1%
тяжёлый 3085
 
20.5%
с 777
 
5.2%
погибшими 777
 
5.2%

Most occurring characters

ValueCountFrequency (%)
й 13482
14.6%
и 12728
13.8%
г 11174
12.1%
Л 10397
11.2%
е 10397
11.2%
к 10397
11.2%
ы 3085
 
3.3%
л 3085
 
3.3%
ё 3085
 
3.3%
ж 3085
 
3.3%
Other values (9) 11609
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 77488
83.7%
Uppercase Letter 14259
 
15.4%
Space Separator 777
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
й 13482
17.4%
и 12728
16.4%
г 11174
14.4%
е 10397
13.4%
к 10397
13.4%
ы 3085
 
4.0%
л 3085
 
4.0%
ё 3085
 
4.0%
ж 3085
 
4.0%
я 3085
 
4.0%
Other values (5) 3885
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
Л 10397
72.9%
Т 3085
 
21.6%
С 777
 
5.4%
Space Separator
ValueCountFrequency (%)
777
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 91747
99.2%
Common 777
 
0.8%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
й 13482
14.7%
и 12728
13.9%
г 11174
12.2%
Л 10397
11.3%
е 10397
11.3%
к 10397
11.3%
ы 3085
 
3.4%
л 3085
 
3.4%
ё 3085
 
3.4%
ж 3085
 
3.4%
Other values (8) 10832
11.8%
Common
ValueCountFrequency (%)
777
100.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 91747
99.2%
ASCII 777
 
0.8%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
й 13482
14.7%
и 12728
13.9%
г 11174
12.2%
Л 10397
11.3%
е 10397
11.3%
к 10397
11.3%
ы 3085
 
3.4%
л 3085
 
3.4%
ё 3085
 
3.4%
ж 3085
 
3.4%
Other values (8) 10832
11.8%
ASCII
ValueCountFrequency (%)
777
100.0%

parent_region
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size222.8 KiB
Москва
14259 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters85554
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowМосква
2nd rowМосква
3rd rowМосква
4th rowМосква
5th rowМосква

Common Values

ValueCountFrequency (%)
Москва 14259
100.0%

Length

2024-01-10T18:17:29.040381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T18:17:29.140541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
москва 14259
100.0%

Most occurring characters

ValueCountFrequency (%)
М 14259
16.7%
о 14259
16.7%
с 14259
16.7%
к 14259
16.7%
в 14259
16.7%
а 14259
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 71295
83.3%
Uppercase Letter 14259
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 14259
20.0%
с 14259
20.0%
к 14259
20.0%
в 14259
20.0%
а 14259
20.0%
Uppercase Letter
ValueCountFrequency (%)
М 14259
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 85554
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
М 14259
16.7%
о 14259
16.7%
с 14259
16.7%
к 14259
16.7%
в 14259
16.7%
а 14259
16.7%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 85554
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
М 14259
16.7%
о 14259
16.7%
с 14259
16.7%
к 14259
16.7%
в 14259
16.7%
а 14259
16.7%

Interactions

2024-01-10T18:17:22.365949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.152668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.797686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.422300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.073331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.734862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.469359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.272920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.900180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.528367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.174566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.838466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.573045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.382585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.011281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.632415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.285219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.943423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.686100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.488494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.116047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.748746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.391865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.057470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.792936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.593494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.222618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.863741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.513314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.169544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.889416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:19.697474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.322737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:20.969131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:21.619971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T18:17:22.264432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T18:17:29.216404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
atmospheric_pressurecloudinessdirection_of_the_windhumiditylightmonthpogoda_regionseveritytemperaturewind_speedyear
atmospheric_pressure1.000-0.1720.097-0.2100.0000.1420.0280.013-0.139-0.1440.126
cloudiness-0.1721.0000.1070.3990.0140.1270.2030.044-0.280-0.0150.097
direction_of_the_wind0.0970.1071.0000.0470.0100.0730.1820.030-0.049-0.0300.092
humidity-0.2100.3990.0471.0000.0380.1870.0820.000-0.2330.0320.066
light0.0000.0140.0100.0381.000-0.0100.0530.0350.062-0.0020.015
month0.1420.1270.0730.187-0.0101.0000.0240.0330.057-0.0020.093
pogoda_region0.0280.2030.1820.0820.0530.0241.0000.1190.0110.4410.152
severity0.0130.0440.0300.0000.0350.0330.1191.0000.0310.0610.066
temperature-0.139-0.280-0.049-0.2330.0620.0570.0110.0311.000-0.1880.142
wind_speed-0.144-0.015-0.0300.032-0.002-0.0020.4410.061-0.1881.0000.082
year0.1260.0970.0920.0660.0150.0930.1520.0660.1420.0821.000

Missing values

2024-01-10T18:17:23.043022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T18:17:23.496323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-10T18:17:23.724822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

yearmonthtemperatureatmospheric_pressurehumiditydirection_of_the_windwind_speedcloudinessweather_conditionslightpointpogoda_regionregionaddressdatetimeseverityparent_region
02021.05.011.0751.6100.0В3.00.00NaNВ темное время суток, освещение включено{'lat': 55.667499, 'long': 37.770245}Юго-востокЛюблиног Москва, ул Верхние Поля, 392021-05-21 00:35:00ЛегкийМосква
12021.05.017.0756.968.0В4.00.20NaNВ темное время суток, освещение включено{'lat': 55.669411, 'long': 37.553995}Юго-западЧеремушкиг Москва, ул Профсоюзная, 562021-05-14 22:30:00ЛегкийМосква
42021.07.023.5758.568.0Штиль, безветрие0.00.95Состояние неба в общем не изменилось.В темное время суток, освещение включено{'lat': 55.7174, 'long': 37.568661}ЦентрХамовникиг Москва, пр-кт Комсомольский, 482021-07-15 21:20:00ЛегкийМосква
112021.07.019.2755.955.0ССЗ1.01.00В темное время суток, освещение не включено{'lat': 55.447467, 'long': 37.133403}Северо-западЮжное ТушиноА-113 Центральная кольцевая автомобильная дорога (Московская область), 239 км2021-07-21 20:36:00ТяжёлыйМосква
152020.08.026.1755.853.0Штиль, безветрие0.00.95В темное время суток, освещение включено{'lat': 55.844982, 'long': 37.424455}Северо-западЮжное Тушиног Москва, ул Туристская, 22020-08-31 19:10:00ЛегкийМосква
172020.08.013.6761.079.0Штиль, безветрие0.00.95В темное время суток, освещение включено{'lat': 55.828775, 'long': 37.530445}СеверКоптевог Москва, ул Академическая Б., 292020-08-20 00:23:00ЛегкийМосква
182020.08.017.3763.988.0Штиль, безветрие0.00.25Дымка.В темное время суток, освещение включено{'lat': 55.833373, 'long': 37.518053}СеверКоптевог Москва, ул Коптевская, 73А СТР 12020-08-08 23:00:00ЛегкийМосква
262020.09.020.6766.136.0ЮВ1.01.00В темное время суток, освещение включено{'lat': 55.755508, 'long': 37.631865}ЦентрТверскойг Москва, пл Старая, 62020-09-04 20:35:00ТяжёлыйМосква
292020.09.011.3758.192.0ЗСЗ1.00.95Дымка.В темное время суток, освещение включено{'lat': 55.784827, 'long': 37.369952}Северо-западСтрогиног Москва, Московская кольцевая автомобильная дорога (МКАД) внешняя сторона, 62 км2020-09-08 23:05:00ЛегкийМосква
332020.09.06.1764.485.0Штиль, безветрие0.00.00В темное время суток, освещение включено{'lat': 55.830167, 'long': 37.552664}СеверТимирязевскийг Москва, ул Тимирязевская, 442020-09-20 22:50:00ЛегкийМосква
yearmonthtemperatureatmospheric_pressurehumiditydirection_of_the_windwind_speedcloudinessweather_conditionslightpointpogoda_regionregionaddressdatetimeseverityparent_region
350102020.011.02.6770.568.0ЗСЗ1.00.6В темное время суток, освещение включено{'lat': 55.768981, 'long': 37.473797}Северо-западХорошево-Мневникиг Москва, наб Карамышевская, 342020-11-10 17:15:00ЛегкийМосква
350122020.011.01.2756.993.0Штиль, безветрие0.01.0Дымка.В темное время суток, освещение включено{'lat': 55.805598, 'long': 37.454077}Северо-западЩукиног Москва, ул Новощукинская, 72020-11-23 19:35:00ТяжёлыйМосква
350142020.011.00.9773.779.0ВЮВ2.01.0Снег с перерывами слабый в срок наблюдения.В темное время суток, освещение включено{'lat': 55.800189, 'long': 37.392172}Северо-западСтрогиног Москва, ул Таллинская, 22020-11-15 18:46:00ЛегкийМосква
350152020.011.06.4767.187.0В1.01.0Дымка.В темное время суток, освещение включено{'lat': 55.769742, 'long': 37.485909}Северо-западХорошево-Мневникиг Москва, наб Карамышевская, 2 12020-11-02 17:10:00ЛегкийМосква
350162020.011.0-1.7769.177.0Ю1.01.0В темное время суток, освещение включено{'lat': 55.864024, 'long': 37.424723}Северо-западСеверное Тушиног Москва, ул Вилиса Лациса, 17 стр. 12020-11-22 04:50:00ЛегкийМосква
350172020.011.06.2763.773.0ЮЮЗ1.00.4В темное время суток, освещение включено{'lat': 55.787234, 'long': 37.479386}Северо-западХорошево-МневникиNaN2020-11-05 17:20:00ЛегкийМосква
350182020.011.00.3772.090.0ЮВ2.01.0Снег непрерывный слабый в срок наблюдения.В темное время суток, освещение включено{'lat': 55.857009, 'long': 37.342669}Северо-западМитиног Москва, ул Барышиха, 442020-11-30 20:00:00ЛегкийМосква
350192020.011.04.1767.889.0В2.01.0Морось незамерзающая непрерывная слабая в срок наблюдения.В темное время суток, освещение включено{'lat': 55.850433, 'long': 37.413415}Северо-западСеверное Тушиног Москва, б-р Яна Райниса, 24 к. 12020-11-01 21:30:00ЛегкийМосква
350202020.011.01.0766.580.0З2.01.0Ливневый снег слабый в срок наблюдения или за последний час.В темное время суток, освещение включено{'lat': 55.802372, 'long': 37.407482}Северо-западСтрогиног Москва, б-р Строгинский, 302020-11-09 21:00:00ЛегкийМосква
350212021.010.09.0773.454.0ЮЗ2.00.0NaNВ темное время суток, освещение включено{'lat': 55.546103, 'long': 37.585237}Юго-западЮжное Бутовог Москва, ш Варшавское, 1962021-10-09 22:53:00ЛегкийМосква